sentiment analysis call fails with cognitive service, returning "HttpOperationError" - sentiment-analysis

Question

text_analytics = TextAnalyticsClient(endpoint=endpoint, credentials=credentials)
documents = [
{
"id": "1",
"language": "en",
"text": "I had the best day of my life."
}
]
response = text_analytics.sentiment(documents=documents)
for document in response.documents:
print("Document Id: ", document.id, ", Sentiment Score: ",
"{:.2f}".format(document.score))
Hi, with the sample code from API manual https://learn.microsoft.com/en-us/azure/cognitive-services/text-analytics/quickstarts/python-sdk#sentiment-analysis
I got the following error while trying to call the sentiment classifier
HttpOperationError Traceback (most recent call last)
<ipython-input-18-f0fb322c9e8c> in <module>
8 }
9 ]
---> 10 response = text_analytics.sentiment(documents=documents)
11 for document in response.documents:
12 print("Document Id: ", document.id, ", Sentiment Score: ",
~/anaconda3/envs/lib/python3.6/site-packages/azure/cognitiveservices/language/textanalytics/text_analytics_client.py in sentiment(self, show_stats, documents, custom_headers, raw, **operation_config)
361
362 if response.status_code not in [200, 500]:
--> 363 raise HttpOperationError(self._deserialize, response)
364
365 deserialized = None
HttpOperationError: Operation returned an invalid status code 'Resource Not Found'

Answer 1

It works for me on my side , pls follow or check the steps below to get started with python sentiment analysis SDK :
Create a text analysis service on Azure portal :
Once created , note its endpoint and either one of two keys.
Try the code below :
from azure.cognitiveservices.language.textanalytics import TextAnalyticsClient
from msrest.authentication import CognitiveServicesCredentials
subscriptionKey = "<your Azure servcice key >"
endpoint = "<your Azure servcice endpoint>"
credentials = CognitiveServicesCredentials(subscriptionKey)
text_analytics = TextAnalyticsClient(endpoint=endpoint, credentials=credentials)
documents = [
{
"id": "1",
"language": "en",
"text": "I had the best day of my life."
}
]
response = text_analytics.sentiment(documents=documents)
for document in response.documents:
print("Document Id: ", document.id, ", Sentiment Score: ",
"{:.2f}".format(document.score))
Result :
Hope it helps .